• 제목/요약/키워드: Statistical tests

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Parametric Tests and Estimation of Mean Change in Discrete Distributions

  • Kim, Jae-Hee;Cheon, Soo-Young
    • Communications for Statistical Applications and Methods
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    • 제16권3호
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    • pp.511-518
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    • 2009
  • We consider the problem of testing for change and estimating the unknown change-point in a sequence of time-ordered observations from the binomial and Poisson distributions. Including the likelihood ratio test, Gombay and Horvath (1990) tests are studied and the proposed change-point estimator is derived from their test statistic. A power study of tests and a comparison study of change-point estimators are done via simulation.

ORDER RESTRICTED TESTS FOR SYMMETRY AGAINST POSITIVE BIASEDNESS

  • Oh, Myong-Sik
    • Journal of the Korean Statistical Society
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    • 제36권3호
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    • pp.335-347
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    • 2007
  • Two new types of positive biasedness, which are closely related to Type III positive biasedness (Yanagimoto and Sibuya, 1972), are proposed. We call these near Type III positive biasedness. Though no implication between Type II and near Type III biasedness exists, near Type III seems to be less restrictive than Type II biasedness. Constrained maximum likelihood estimates of distribution functions under near Type III positive bisedness are obtained. The likelihood ratio tests of symmetry against new positive biasedness restrictions are proposed. A small simulation study is conducted to compare the performance of the tests.

OBJECTIVE BAYESIAN APPROACH TO STEP STRESS ACCELERATED LIFE TESTS

  • Kim Dal-Ho;Lee Woo-Dong;Kang Sang-Gil
    • Journal of the Korean Statistical Society
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    • 제35권3호
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    • pp.225-238
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    • 2006
  • This paper considers noninformative priors for the scale parameter of exponential distribution when the data are collected in step stress accelerated life tests. We find the Jeffreys' and reference priors for this model and show that the reference prior satisfies first order matching criterion. Also, we show that there exists no second order matching prior in this problem. Some simulation results are given and we perform Bayesian analysis for proposed priors using some data.

On Combination of Several Weighted Logrank Tests

  • Park, Sang-Gue;Jeong, Gyu-Jin
    • Communications for Statistical Applications and Methods
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    • 제2권2호
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    • pp.213-220
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    • 1995
  • We consider a class of the weighted logrank tests and 4 types of weights in this class. We propese a test based on the maximum of 4 weighted logrank statistics and suggest a simulation techniqur to obtain the p-value of proposed test. It is shown through the simulation studies that the proposed test is robust and has reasonably good powers comparing with the well known efficient tests.

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A Bayesian Test Criterion for the Multivariate Behrens-Fisher Problem

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • 제28권1호
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    • pp.107-124
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    • 1999
  • An approximate Bayes criterion for multivariate Behrens-Fisher problem is proposed and examined. Development of the criterion involves derivation of approximate Bayes factor using the imaginary training sample approach introduced by Speigelhalter and Smith (1982). The criterion is designed to develop a Bayesian test, so that it provides an alternative test to other tests based upon asymptotic sampling theory (such as the tests suggested by Bennett(1951), James(1954) and Yao(1965). For the derived criterion, numerical studies demonstrate routine application and give comparisons with the classical tests.

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Assessing the Accuracy of Outlier Tests in Nonlinear Regression

  • Kahng, Myung-Wook;Kim, Bu-Yang
    • Communications for Statistical Applications and Methods
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    • 제16권1호
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    • pp.163-168
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    • 2009
  • Given the specific mean shift outlier model, the standard approaches to obtaining test statistics for outliers are discussed. Accuracy of outlier tests is investigated using subset curvatures. These subset curvatures appear to be reliable indicators of the adequacy of the linearization based test. Also, we consider obtaining graphical summaries of uncertainty in estimating parameters through confidence curves. The results are applied to the problem of assessing the accuracy of outlier tests.

A Comparison on the Empirical Power of Some Normality Tests

  • Kim, Dae-Hak;Eom, Jun-Hyeok;Jeong, Heong-Chul
    • Journal of the Korean Data and Information Science Society
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    • 제17권1호
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    • pp.31-39
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    • 2006
  • In many cases, we frequently get a desired information based on the appropriate statistical analysis of collected data sets. Lots of statistical theory rely on the assumption of the normality of the data. In this paper, we compare the empirical power of some normality tests including sample entropy quantity. Monte carlo simulation is conducted for the calculation of empirical power of considered normality tests by varying sample sizes for various distributions.

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Minimum Hellinger Distance Bsed Goodness-of-fit Tests in Normal Models: Empirical Approach

  • Dong Bin Jeong
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.967-976
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    • 1999
  • In this paper we study the Hellinger distance based goodness-of-fit tests that are analogs of likelihood ratio tests. The minimum Hellinger distance estimator (MHDE) in normal models provides an excellent robust alternative to the usual maximum likelihood estimator. Our simulation results show that the Hellinger deviance test (Simpson 1989) based goodness-of-fit test is robust when data contain outliers. The proposed hellinger deviance test(Simpson 1989) is a more direcct method for obtaining robust inferences than an automated outlier screen method used before the likelihood ratio test data analysis.

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Stationary bootstrapping for structural break tests for a heterogeneous autoregressive model

  • Hwang, Eunju;Shin, Dong Wan
    • Communications for Statistical Applications and Methods
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    • 제24권4호
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    • pp.367-382
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    • 2017
  • We consider an infinite-order long-memory heterogeneous autoregressive (HAR) model, which is motivated by a long-memory property of realized volatilities (RVs), as an extension of the finite order HAR-RV model. We develop bootstrap tests for structural mean or variance changes in the infinite-order HAR model via stationary bootstrapping. A functional central limit theorem is proved for stationary bootstrap sample, which enables us to develop stationary bootstrap cumulative sum (CUSUM) tests: a bootstrap test for mean break and a bootstrap test for variance break. Consistencies of the bootstrap null distributions of the CUSUM tests are proved. Consistencies of the bootstrap CUSUM tests are also proved under alternative hypotheses of mean or variance changes. A Monte-Carlo simulation shows that stationary bootstrapping improves the sizes of existing tests.

Tests of equality of several variances with the likelihood ratio principle

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • 제25권4호
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    • pp.329-339
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    • 2018
  • In this study, we propose tests for equality of several variances with the normality assumption. First of all, we propose the likelihood ratio test by applying the permutation principle. Then by using the p-values for the pairwise tests between variances and combination functions, we propose combination tests. We apply the permutation principle to obtain the overall p-values. Also we review the well- known test statistics for the completion of our discussion and modify a statistic with the p-values. Then we illustrate proposed tests by numerical and simulated data and compare their efficiency with the reviewed ones through a simulation study by obtaining empirical p-values. Finally, we discuss some interesting features related to the resampling methods and tests for equality among several variances.